Existing map-matching approaches face challenges in performing online trajectory identification. Such approaches utilize algorithms that are energy-inefficient to and/or inaccurate. For example, approaches that include a high global positioning system (GPS) sampling rate lead to redundant GPS points for use in an algorithm, resulting in energy wastage. Conversely, approaches that include a low GPS sampling rate lead to insufficient GPS points for use in an algorithm, resulting in low accuracy levels.
Accordingly, a need exists for location sampling techniques for map-matching in coordination with requirements of a given matching algorithm.